Automated method development in high-pressure liquid chromatography
•Method development in chromatography is complex, time-consuming and expensive.•Automated methods facilitate and speed up the method development process.•A separation can be mathematically described as an optimization problem.•Experimental and model-based approaches exist to solve the optimization p...
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Veröffentlicht in: | Journal of Chromatography A 2024-01, Vol.1714, p.464577, Article 464577 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Method development in chromatography is complex, time-consuming and expensive.•Automated methods facilitate and speed up the method development process.•A separation can be mathematically described as an optimization problem.•Experimental and model-based approaches exist to solve the optimization problem.•Methods for automated peak detection and peak tracking allow complete automation.
Method development in liquid chromatography is a crucial step in the optimization of analytical separations for various applications. However, it is often a challenging endeavour due to its time-consuming, resource intensive and costly nature, which is further hampered by its complexity requiring highly skilled and experienced scientists. This review presents an examination of the methods that are required for a completely automated method development procedure in liquid chromatography, aimed at taking the human out of the decision loop. Some of the presented approaches have recently witnessed an important increase in interest as they offer the promise to facilitate, streamline and speed up the method development process. The review first discusses the mathematical description of the separation problem by means of multi-criteria optimization functions. Two different strategies to resolve this optimization are then presented; an experimental and a model-based approach. Additionally, methods for automated peak detection and peak tracking are reviewed, which, upon integration in an instrument, allow for a completely closed-loop method development process. For each of these approaches, various currently applied methods are presented, recent trends and approaches discussed, short-comings pointed out, and future prospects highlighted. |
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ISSN: | 0021-9673 1873-3778 |
DOI: | 10.1016/j.chroma.2023.464577 |